Abstract

In this paper, a convex filled function method for solving constrained global optimization problems is proposed. A convex filled function is proposed by combining the idea of filled function in unconstrained global optimization and the idea of penalty function in constrained optimization. Then a convex filled function method for obtaining a global minimizer or an approximate global minimizer of the constrained global optimization problem is presented. Some numerical results demonstrate the efficiency of this global optimization method for solving constrained global optimization problems.

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